An Evolutionary Game Analysis of Stakeholders' Decision-Making Behavior in Medical Data Sharing

In the era of big data, medical data sharing has become an inevitable requirement to improve the quality and efficiency of medical services. To advance the progress of medical data sharing and expedite the circulation of data value, it becomes crucial to examine the decision-making behavior of stakeholders involved in the medical-data-sharing process. To this end, we construct a three-way evolutionary game model applicable to the medical sharing scenario, analyzing the evolutionary trends in the selection strategies of data providers, the medical-data-sharing platform and data demanders. Furthermore, through theoretical analysis and simulation experiments, we explore the game equilibrium point of the system and analyze key factors that affect stakeholder strategy selection. The results of the experiment show that, in addition to data security, platforms and regulators should pay attention to the regulation and governance of the quality of data flows, which involves reasonable incentives-feedback-rewards and penalties. By strengthening the security technology and data governance system construction of sharing platforms, as well as promoting regulatory authorities to implement reward and punishment measures, etc., a stable state can be achieved in such systems. In addition, this article also proposes relevant management suggestions for medical data sharing in order to provide useful references for scientific decision making by stakeholders.